Object detection and segmentation is a well-studied problem for natural scene images, but those objects are generally much larger and suffer minimally from distortions exacerbated in overhead imagery. Natural scene research is driven by datasets such as MSCOCO [1]} and PASCALVOC [2]}, but those datasets lack multiple views of each object. PASCAL3D [3]}, autonomous driving datasets such as KITTI [4]}, CityScapes [5]}, existing multi-view datasets [6]}, [7]}, and tracking datasets such as MOT2017[8]} or OBT [9]} contains different views but are confined to a narrow range of angles, lack sufficient heterogeneity to test generalization between views, and are restricted to natural scene images. Multiple viewpoints are found in 3D model datasets [10]}, [11]}, but those are not photorealistic and lack the occlusion and visual distortion properties encountered with real imagery.
